information sharing

With growing use of interorganizational systems, the scope of interfirm collaboration has increased considerably, particularly in the supply chain context. An important prerequisite of interfirm collaboration is information sharing. Extant research suggests clear advantages of information sharing. The research at hand addresses antecedents of interorganizational information sharing. Based on findings from interorganizational systems adoption and interfirm collaboration research, a structural model is developed and validated by a quantitative survey among Austrian retailers and manufacturers in the fast-moving consumer-goods sector. The proposed model analyzes the effect of internal factors (commitment, information policy, and technical readiness), interorganizational factors (relationship, trust, power, and trading partners' technical readiness), and economic factors (perceived benefits and costs) on information-sharing behavior. The results show the relevance of internal factors and perceived benefits. The study reveals particularities of information-sharing behavior and can help practitioners to understand what motivates their trading partners to share information. [Article copies are available for purchase from InfoSci-on-Demand.com]

Keywords: Business to Business (B2B); Electronic Collaboration; Interorganizational Systems; Supply Chain Management; Trading Partners

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Introduction

In the last years, the intensity of efforts for an enhanced collaboration between firms in supply chains has increased. Interorganizational systems (IOS), that is, electronic linkages between trading partners that can eliminate manual information transfer, have largely contributed to this paradigm shift as they proved to be technological enablers for closer relationships and tighter coordination between trading partners. Collaboration techniques such as vendor-managed inventory rely on regular sharing of information between the engaged firms (Angulo, Nachtmann, & Waller, 2004). As Lee, Padmanabhan, and Whang (1997) and Simchi-Levi, Kaminsky, and Simchi-Levi (2000) argue, interorganizational information sharing can contribute considerably to a reduction of the bullwhip effect, a distortion in the supply chain that increases with growing distance from the final consumer. In doing so, IOS has evoked changes in business processes across organizations.

Each business transaction requires a minimum of information exchange (i.e., placing an order, sending an invoice). Information exchanged between organizations that exceeds the minimum information is referred to as information sharing. Hence, information sharing denotes the regular exchange of data that goes beyond the transmittal of data necessary in any cross-organizational trading (Madlberger, 2008). Information sharing addresses a key problem in every supply chain, that is, the information asymmetry between trading partners. While the stock level of the supply chain is determined by upstream supply chain partners, these organizations are less informed about market demand than their downstream trading partners (e.g., retailers). Thus, the more poorly informed partners influence the stock level of the better informed players (Chu & Lee, 2006).

Information sharing can be considered a multidimensional construct that involves four dimensions of information characteristics: (a) the content, that is, the type of information shared (e.g., point-of-sales [POS] data), (b) the frequency of information shared (e.g., daily vs. monthly data), (c) the granularity of information shared (i.e., how detailed or aggregated the information is), and (d) the up-to-dateness of the information shared (e.g., data from a current period vs. past periods). Although information sharing does not have to be conducted electronically, it will hardly be economically justifiable if it does not involve IOS.

Game-theoretic research has clearly demonstrated the benefits of information sharing (e.g., Diaz & Buxmann, 2003; Gavirneni, 2002; Lee et al., 1997; Lee, So, & Tang 2000). These findings suggest that firms should at least consider it. Information sharing is, however, by its nature an interorganizational activity that depends not only on one's own intention to participate, but also on trading partners' willingness and ability. As a consequence, firms need to understand why and under which circumstances their trading partners are ready to share information. To give practically relevant recommendations about appropriate participation in information sharing and about trading partners that are advisable to share information with, we need a better understanding about motivations and drivers of information sharing. If firms realize why their trading partners show a particular information-sharing behavior, it is easier for them to pursue an appropriate information-sharing policy. Also, expectations of trading partners can better be understood. The research questions of this study are the following:

* To what extent do internal antecedents impact a firm's participation in information sharing?

* To what extent do interorganizational antecedents impact a firm's participation in information sharing?

* To what extent do perceived benefits and costs impact a firm's participation in information sharing?

These research questions are aimed to be answered by an empirical study in the Austrian fast-moving consumer goods (FMCG) sector. The article is organized as follows. In the next section, a literature review on characteristics and benefits of information sharing is provided. Then the research model and hypotheses are developed. In the subsequent sections, the research methodology and the study results are presented before the findings are discussed in detail. Finally, a contribution statement, study limitations, and implications for research and practice are provided.

Interorganizational information Sharing

In literature, several researchers have addressed information sharing as a behavioral concept in supply chains. One stream of research refers to different levels or categories of information sharing while other researchers point at concrete examples of information sharing. Within the first approach, Lee and Whang (2000) distinguish three system models for information sharing. In the information-transfer model, a firm transmits information directly to a trading partner that maintains the database for decision making. In the third-party model, an intermediary collects the information, supports the transactions, and maintains the database. The information-hub model has the same structure as the third-party model except that the third party is replaced by a system. Seidmann and Sundararajan (1998) distinguish four levels of information sharing. The order information exchange is the simplest form as it only covers electronic transfer of information that is contained by orders. Strictly speaking, this level is not considered information sharing. Operational information sharing includes the transmittal of information on an operative level exceeding order information, such as inventory levels. The sharing of strategic information requires long-term contractual agreements. Finally, strategic and competition information sharing involves competing firms, for example, by sharing market information. Information sharing can also be categorized according to the type of information shared (Lee & Whang). Information sharing on the inventory level can contribute to a decrease of necessary safety stock levels and is the basis of many collaboration models. The transmittal of sales data is related to consumer behavior and can help in avoiding the bullwhip effect. Order status information supports tracking and tracing. Sales forecast data sharing improves inventory management by exploiting the market expertise of downstream trading partners. The sharing of production and delivery schedules can optimize production planning along the entire supply chain. Any information shared can further be characterized according to the quality, that is, up-to-dateness, accuracy, and completeness (Angulo et al., 2004).

The second approach addresses the content of data that is subject to information sharing, that is, an operationalization of information sharing. In Table 1, an overview of information-sharing operationalizations discussed in literature is provided.

Literature has thoroughly examined the benefits associated with information sharing. Simulations have quantified the extent of benefits for individual players in a supply chain. Information sharing can yield considerable advantages for firms, particularly by reducing costs, improving service levels, and reducing lead times and stockouts (Angulo et al., 2004). Particularly, the positive impact of information sharing on the elimination of the bullwhip effect could be demonstrated (Chen, Drezner, Ryan, & Simchi-Levi, 2000; Lee et al., 1997; Simchi-Levi et al., 2000). Also, empirical research reports the positive impact of an intensive relationship including information sharing on a firm's performance (Narasimhan & Nair, 2005).

Information sharing relies on the existence of IOS as it is a technical prerequisite and provides an economic justification of information-sharing-based collaboration. IOS may be applied on a bilateral basis between two organizations or within networks in supply chains. The latter approach is also referred to as business networking (Oesterle, Fleisch, & Alt, 2001) and denotes interorganizational collaboration in supply chains based on an integration of IOS (Winter, 2003). It requires embedding interorganizational collaboration into the corporate strategy, business processes, and existing information systems (Alt & Fleisch, 2001). Thus, business networking distinguishes between a strategic (i.e., a long-term collaboration agreement with trading partners) and an operational (i.e., process level) perspective. On the IT level, the collaborating firms agree on applications and data, but also on the electronic communication (Alt & Fleisch).

As Grover and Saeed (2007) show empirically, there is a strong impact of an open information-sharing environment on the integration of IOS. The use of IOS can be a basis of interfirm collaboration (see Kumar & van Dissel, 1996, for a review). Thus, the uses of IOS, collaboration, and participation in information sharing have many characteristics in common. Like information sharing, IOS-based collaboration has turned out to be a source of various kinds of benefits to firms (Barrett & Konsynski, 1982; Da Silveira & Cagilano 2006; Sanders & Premus, 2005). As Mukhopadhyay and Kekre (2002) have shown, IOS-based collaboration can provide both operational benefits, that is, the reduction of paperwork, and strategic benefits by launching interfirm collaboration. Thus, information sharing is a key to obtaining particularly strategic benefits by using IOS. Like IOS application, information sharing also involves the cooperation and commitment of all participating firms (Premkumar & Ramamurthy, 1995). Patnayakuni and Seth (2006) analyzed the impact of IT integration capabilities on firm performance, mediated by supply chain process integration. Their study revealed that all these relationships are significant.



The motivation to use IOS, in particular electronic data interchange (EDI), has been subject to many studies in IS research. In an early study, Grover (1993) identified competitive need, proactive technological orientation, internal push, market assessment, impediments, and industry adoption as antecedents of IOS use. Premkumar, Ramamurthy, and Nilakanta (1994) and Iacovou, Benbasat, and Dexter (1995) pointed at relative advantage, costs, and technical compatibility as drivers of IOS use. Later, organizational and power-related issues were addressed. Premkumar and Ramamurthy (1995) and Premkumar, Ramamurthy, and Crum (1997) successfully investigated the roles of competitive pressure, exercised power, internal need, top-management support, customer support, and firm size. Hart and Saunders (1997) focused on power and demonstrated the impact of trading partners' dependence, persuasive and coercive power, trust, and continuity as antecedents of IOS use. Ramamurthy, Premkumar, and Crum (1999) distinguished between internal antecedents (internal support, IOS benefit potential, IOS compatibility, and resource intensity) and interorganizational factors (customer support and competitive pressure). The role of expected benefits was first considered by Chwelos, Benbasat, and Dexter (2001). Similarly, researchers also investigated drivers and benefits of interfirm collaboration (e.g., Holweg, Disney, Holmstrom, & Smaros, 2005; see Elgarah, Falaleeva, Saunders, Ilie, Shim, & Courtney, 2005, for a comprehensive literature review). Lin (2006) developed a framework based on widespread theories to explain conceptually why firms can obtain benefits from collaboration.

Research Model and Hypotheses Development

The dependent variable in the research model is information-sharing behavior. It investigates to what extent a firm shares information with its most important trading partners. The model refers to information sharing on the second and third level of Seidmann and Sundararajan's (1998) information-sharing intensity classification and distinguishes between operational and strategic information sharing. Operational information is characterized as being short-term, quantitative information about daily logistics and sales activities or status information on orders and inventory levels. Its main purpose is reducing order cycle times and inventory levels, and improving customer service. Strategic information is related to long-term issues in marketing, logistics, and other business strategies. It is necessary for carrying out interfirm collaboration and other strategic logistics decisions (Moberg et al., 2002).

Antecedents of information sharing are separated into internal, interorganizational, and economic factors. The separation between internal and interorganizational factors has been made frequently in IS research on IOS adoption (e.g., Premkumar & Ramamurthy, 1995; Ramamurthy et al., 1999). To account for the strong impact of the economic perspective that has been identified in IOS adoption research (Chwelos et al., 2001; Iacovou et al.; Morrell & Ezingeard, 2002; Premkumar et al., 1994), we apply perceived benefits and costs as additional antecedents of information sharing. Although Iacovou et al. (1995) attribute benefits to the organizational level, they consider it distinct from organizational readiness. In our study, the economic factors are separated from the internal factors as they are related to the firms' perceptions of information-sharing behavior's result. In other words, the estimation of perceived benefits and costs requires considering its expected consequences given information sharing is already practiced. In contrast, the internal variables do not require thinking of an outcome of information sharing and are therefore considered conceptually different from the economic factors.

The impact of the suggested antecedents on information sharing behavior is grounded in several theoretical bases. The theoretical approaches applied in this research are appropriate for the analysis of IOS use and interorganizational collaboration (Lin, 2006). We discuss the resource-based view (RBV) of the firm, social exchange theory, the theory of embeddedness, and transaction-cost economics (TCE). In the following, the hypothesized impacts of internal factors, interorganizational factors, and economic factors are discussed and their respective theoretical backgrounds are elaborated.

Internal Factors

Like the application of IOS, information sharing can strongly affect the entire firm. Hence, it is likely that internal factors influence this decision. Due to the linkages between IOS use and information sharing, we posit that there are technical and organizational factors that form an internal predisposition to information sharing (Ramamurthy et al., 1999).

The consideration of the internal factors stems from the resource-based view of the firm, which explains how appropriate resources can contribute to competitive advantages. In particular, appropriate resources need to be valuable, rare, difficult to imitate, and nonsubstitutable (Barney, 1991). The kind of resources involved can be very heterogeneous; for example, Wade and Hulland (2004) mention competencies, skills, assets, strategic assets, and stocks. Kleinschmidt, de Brentani, and Salomo (2007) regard organizational resources as resources in the sense of RBV and apply attitude to resource commitment, top-management involvement, global-innovation culture, and process formality. The following internal factors meet the requirements of RBV and thus can also be considered resources.

An important internal factor identified in prior research is top-management commitment. It is an important organizational resource as it (a) provides necessary knowledge and capability, and (b) ensures that necessary investments and efforts are made available (Kleinschmidt et al., 2007). Particularly due to necessary investments and changes within the firm, information sharing is expected to encounter much resistance if it is not supported by top management (Moberg et al., 2002). Only top management can send the right signals to the affected parts of the organization. Top-management support is also required for convincing trading partners to participate in information sharing (Ramamurthy et al., 1999). Therefore, we hypothesize the following.

[H.sub.1a]: Top-management commitment will positively impact strategic information-sharing behavior.

[H.sub.1b]: Top-management commitment will positively impact operational information-sharing behavior.

An organizational factor that is considered relevant for information-sharing participation in particular is a firm's general information policy. Each firm decides its level of transparency toward its trading partners and other stakeholders. A firm's willingness to disseminate information outside its boundaries to stakeholders is considered to ease or hinder information sharing. Previous research stressed the relevance of external communication and therefore transparency for the success of partnerships (Mohr & Nevin, 1990; Mohr & Spekman, 1994). From an RBV-based point of view, the concept of corporate culture (Denison, 1984) becomes relevant. Corporate culture refers to "norms, attitudes, vales, and behavior patterns" (Kleinschmidt et al., 2007, p. 423). It is an organizational resource that is generated over years; it is hard to imitate and cannot be shared with competitors. Thus, Helfat and Peteraf (2003) argue that corporate culture can also be regarded as a resource. A firm's information policy can be considered a part of corporate culture as it refers to the general attitudes and behavior patterns of informational behavior. Thus, in analogy to commitment, we posit that an active information policy positively impacts information-sharing behavior.

[H.sub.2a]: An active information policy will positively impact strategic information-sharing behavior.

[H.sub.2b]: An active information policy will positively impact operational information-sharing behavior.

From a technological point of view, information sharing requires the availability of IOS. Internal readiness denotes the existence of appropriate electronic links to trading partners (Bharadwaj, Sambamurthy, & Zmud 1998). Information systems have successfully been discussed as resources in the sense of RBV as they can meet the criteria of value, rarity, inimitability, and nonsubstitutability (see Wade & Hulland, 2004, for a literature review). As IOS is expected to be a strong facilitator of information sharing, we hypothesize that firms that have the necessary technical prerequisites are more likely to engage in information sharing.

[H.sub.3a]: Internal technical readiness will positively impact strategic information-sharing behavior.

[H.sub.3b]: Internal technical readiness will positively impact operational information-sharing behavior.

Interorganizational Factors

On the interorganizational level, findings from social exchange theory can be applied. This theory seeks to explain why individuals behave in a way that is favorable to others without knowing what the exact future return will be (Kankanhalli, Tan, & Wei, 2005). Social exchange theory allows the elaboration of trust and power as relevant conditions in a relationship among individuals or organizations (Hart & Saunders, 1997). Similarly, the theory of embeddedness describes the characteristics of a highly integrated relationship among organizations and demonstrates the crucial role of trust, relationship, and power for the adoption of IOS (Chatfield & Yetton, 2000; Uzzi, 1997).

Trust is referred to as the belief that a partner will take favorable actions and that there will be no unexpected activities that could evoke negative consequences (Anderson & Narus, 1990). Hence, trust inherits some degree of voluntary vulnerability for the partner. Information sharing is such a behavior. In the case of information dissemination, a firm bears the risk that the information is abused. In the case of information receipt, the firm is exposed to the risk that the information is incorrect (Moberg et al., 2002). According to the theory of embeddedness, trust is a key attribute of an embedded relationship. It reinforces the exchange of sensitive information and joint problem solving (Uzzi, 1997). Therefore, we consider the following impact of trust on information sharing.

[H.sub.4a]: Trust in the trading partners will positively impact strategic information-sharing behavior.

[H.sub.4b]: Trust in the trading partners will positively impact operational information-sharing behavior.

The relationship between firms has been investigated in several contexts to explain IOS adoption intention or benefits obtained by IOS use. Like IOS application, information sharing is highly dependent on interfirm agreements and a joint commitment. These factors provide the necessary conditions for information sharing and related IT investments (Uzzi, 1997). An embedded relationship with trading partners is characterized by its focus on long-term collaboration, its intensity, and its average time horizon (Moberg et al., 2002), but also on the role of contractual obligations. Derived from the theory of embeddedness, which postulates that the information exchange is higher in an embedded relationship, we hypothesize the following.

[H.sub.5a]: A highly embedded relationship with trading partners will positively impact strategic information-sharing behavior.

[H.sub.5b]: A highly embedded relationship with trading partners will positively impact operational information-sharing behavior.

In the context of social exchange theory, literature has revealed the high importance of relative power between trading partners. The concept of power was put forward by Hart and Saunders (1997) and Bakos and Brynjolfsson (1993). Research on EDI adoption demonstrated that competitive pressure (Premkumar et al., 1997) and exercised power (Hart & Saunders) are key drivers for EDI adoption. Therefore, powerful organizations can enforce a certain behavior by its trading partners. In the present study, it is investigated whether power influences information-sharing behavior. In this context, the trading partners' relative power is of interest. It is measured by a firm's perception that it depends on the trading partners and that they can influence internal decisions.

Derived from research on IOS adoption, we posit that information sharing will be fostered by powerful firms that can influence other firms' information-sharing decisions. Powerful players are often early adopters of information systems innovations and tend to impose them on trading partners, for example, as Wal-Mart did after it had implemented the RFID (radio-frequency identification) technology (Centrale fur Coorganisation [CCG], 2004). As information sharing is an interorganizational activity, we conclude that powerful firms tend to be interested in information-sharing participation with its trading partners.

[H.sub.6a]: Trading partners' relative power will positively impact strategic information-sharing behavior.

[H.sub.6b]: Trading partners' relative power will positively impact operational information-sharing behavior.

From a technological point of view, a firm that is willing to share information might be hindered from it due to a lack of its trading partners' technological capabilities. Trading partners' information technologies are a resource that is necessary for information sharing. As discussed by Chatfield and Yetton (2000), a relationship that is characterized by an intensive exchange of information shows a higher level of IOS application. Therefore, we regard the trading partners' technical readiness as a further interorganizational antecedent of information-sharing behavior that is operationalized in an analogous way to internal technical readiness.

[H.sub.7a]: Trading partners' technical readiness will positively impact strategic information-sharing behavior.

[H.sub.7b]: Trading partners' technical readiness will positively impact operational information-sharing behavior.

Economic Factors

Economic factors have largely been investigated in the context of information systems application and IOS adoption (Chwelos et al., 2001; Iacovou et al., 1995; Morrell & Ezingeard, 2002; Premkumar et al., 1994). The idea behind this consideration is the assumption that such measures imply costs and considerable investments and are therefore subject to cost-benefit evaluation. Also, information sharing may require further improvements and adaptations to IOS as well as management efforts that can evoke further costs. Furthermore, considerations on security or agreements concerning data formats, transmittal intervals, data granularity, or other issues will have to be determined.

Transaction-costs economics addresses this issue by investigating the impact of transaction costs on coordination mechanisms (Williamson, 1975). It is assumed that firms will share more information if they are in a highly integrated relationship (as also described by the theory of embeddedness). Increased information sharing is therefore likely to increase transaction costs. On the other hand, according to TCE, a high integration also shows favorable consequences, for example, a higher coordination between trading partners, which may improve their joint reaction to external developments such as consumer demand. Examples of such beneficial effects are lower inventory levels, higher delivery accuracy, or sales increase due to less out-of-stock situations. In this way, information sharing would contribute to the achievement of benefits to the involved organizations. As information sharing is therefore associated both with benefits and costs to the involved organizations, we can hypothesize for profitoriented organizations the following.

[H.sub.8a]: Perceived benefits of information sharing will positively impact an organization's strategic participation.

[H.sub.8b]: Perceived benefits of information sharing will positively impact an organization's operational participation.

[H.sub.9a]: Perceived costs of information sharing will negatively impact an organization's strategic participation.

[H.sub.9b]: Perceived costs of information sharing will negatively impact an organization's operational participation.

In Figure 1, the hypotheses in the research model are summarized graphically.

ResearCh Methodology



To test the research model and its hypotheses, a quantitative survey among firms in the Austrian FMCG industry has been conducted. This sector was chosen because it shows a high delivery and order frequency, thus reaching a critical mass for IOS use and collaboration. As many goods are perishable, logistics processes are complex. The Austrian FMCG market shows some particularities that are typical for a small country (8 million inhabitants) and thus evokes differences to large markets such as the United States. During the last years, a strong tendency toward consolidation among retailers could be observed, which contributed to an increased power of retailers over suppliers. Furthermore, the industry experienced a strong growth of discounters, particularly in the groceries industry. While there are few strong and many small retailers in the market, the supplier side is more homogenous. Dominant players are international brand manufacturers that are competing with mid-size local manufacturers. Most large retailers as well as numerous large and medium-sized manufacturers are expanding to the Eastern European countries; hence, many firms are export oriented. Due to the small size of the market, there is little anonymity between firms. Managers on both sides know each other very well and therefore personal contacts play a major role in the Austrian market.


The research sample contained both manufacturers and retailers. The questionnaire was developed based on a thorough literature research and validations by experts in academia and practice. All items were developed in English and translated into German by a German native speaker. To avoid a language bias, the items were back-translated by an English native speaker. The comparison with the original items resulted in minor corrections of the wording. Before the survey period started, the questionnaire was pretested with five practitioners from the FMCG sector, which led to small adjustments and the elimination of one question outside the research model.

The written questionnaire was sent via a mailing to approximately 2,000 firms in June 2006. The addresses were obtained from the leading Austrian yellow-pages provider, Herold Business Data. The target persons were the general managers and CEOs, who were addressed personally. In the cover letter, managers were requested to forward the questionnaire to competent employees, if necessary. In October 2006, a follow-up mailing took place and the questionnaire was advertised in the Austrian GS1 quarterly newsletter in December 2006. A total of 223 firms responded to the questionnaire, out of which 62 were incomplete and thus eliminated from further analysis. Therefore, a sample of 161 questionnaires was used for model testing, which results in a response rate of 8.1%. This level is within the range of surveys among organizations where lower response rates are occurring frequently (Rogelberg & Stanton, 2007). The sample description is shown in Table 2 (percentages refer to the completed questionnaires; thus n = 161).

Research variables were measured by multi-item scales that were applied by previous research or developed by the author. All items applied a seven-point Likert scale ranging from 1 (totally agree) to 7 (totally disagree). The seven-point scale was chosen instead of a five-point scale because the participants of the pretest recommended applying more answer categories to allow the answers to be distinguished in a finer way. For all questions concerning interorganizational variables (i.e., trust, power, relationship, and trading partners' readiness, as well as for information-sharing behavior), the respondents were requested to consider their five most-important trading partners. In Table 3, the used multi-item measurement scales are presented together with their numbers of items and the reliabilities (Cronbach's alpha). The values are all above the recommended level of 0.7. The measurement items and their sources are shown in detail in the appendix.

Study Results

In this section, the results of model testing are presented. The model was tested by means of a partial least squares (PLS) analysis. This method was preferred to structural equation modeling (SEM) for several reasons. First, SEM requires the manifest variables to be multivariate normal distributed. A Kolmogorov-Smirnoff test revealed that this assumption failed. The sample size is rather small, which is another argument for PLS analysis. Third, as Teo, Wei, and Benbasat (2003) suggest, PLS is considered more appropriate for research models that are in an early stage of development and therefore have not yet been tested extensively. The analysis was carried out by the open-source software SmartPLS provided by the University of Hamburg (Ringle, Wende, & Will, 2005). To calculate the significance of the path coefficients, a bootstrapping procedure was applied that yielded T values (Rai, Patnayakuni, & Seth, 2006). Path coefficients with T values higher than 1.65 are significant at a 5% level. Table 4 shows the results of the PLS analysis.

Discussion

The PLS analysis shows that several internal variables as well as the perceived benefits of information sharing show a significant impact on information-sharing behavior. [H.sub.1a] and [H.sub.1b] postulated that top-management commitment would impact strategic and operational information sharing. [H.sub.1a] yielded a significant path coefficient of 0.268, which is the strongest relationship in the model. Hence, the impact of top-management commitment on strategic information sharing could be confirmed. This result is consistent with prior findings on the role of commitment for the adoption of IOS (e.g., Ramamurthy et al., 1999; Soliman & Janz, 2004). In contrast, the impact of commitment on operational information sharing ([H.sub.1b]) is not supported by data. A possible explanation of this unexpected result could be the decision competence of different management levels within an organization. Strategic information sharing is expected to be determined on the topmanagement level. The decision on sharing of operational information, however, might also be made by department managers, thus the commitment of the surveyed senior-management level could play a minor role in this respect. This assumption, however, requires further empirical investigation.



Hypotheses [H.sub.2a] and [H.sub.2b] assumed a significant impact of corporate information policy on strategic and operational information sharing. Both hypotheses could be confirmed. [H.sub.2a] shows a path coefficient of 0.265, and [H.sub.2b] a path coefficient of 0.237. Therefore, the newly introduced variable shows a significant positive impact on information-sharing behavior. This result implies for practice that firms seem to have a general attitude toward the dissemination of information in several dimensions, which also plays a significant role for information-sharing behavior. If a firm's information policy is known, this might help to predict its willingness to share information.

The next two hypotheses, [H.sub.3a] and [H.sub.3b], predicted an impact of internal technical readiness on information-sharing behavior. While this relationship is supported by data in the context of operational information sharing ([H.sub.3b]), there is no significant impact on strategic information sharing ([H.sub.3a]). The path coefficient of [H.sub.3b] is 0.257. The result allows the conclusion that high technical readiness may be a prerequisite for operational information sharing, while it is not for strategic information sharing. This discrepancy could lie in different natures of strategic and operational data. While operational data are usually highly standardized and formatted, strategic data (e.g., plans or marketing strategies) are often less structured, which reduces the dependence on appropriate IOS.

The next eight hypotheses are related to interorganizational variables. As the results in Table 3 show, none of the hypothesized impacts are significant, which is an unexpected outcome. [H.sub.4a] and [H.sub.4b] investigated the influence of trust on information-sharing behavior. Although there is a stronger impact of trust on operational information sharing, there is no significant indication that this relationship exists in practice. Similarly, no impact of relationship on information-sharing behavior ([H.sub.5a] and [H.sub.5b]) could be observed. As a consequence, the considerations based on social exchange theory and the theory of embeddedness are different from the findings in the survey. [H.sub.6a] and [H.sub.6b] stated that there would be a positive impact of trading partners' power on information-sharing behavior. This relationship also could not be supported. Finally, [H.sub.7a] and [H.sub.7b] are also rejected. There is no impact of trading partners' technical readiness on a firm's information-sharing behavior.

Although previous studies on IOS adoption were conducted with similar methods and variables (Chwelos et al., 2001; Premkumar & Ramamurthy, 1995; Premkumar et al., 1997; Premkumar et al., 1994; Ramamurthy et al., 1999), this result is different from those findings. There may be several reasons for that. First, information sharing is obviously conceptually different from IOS adoption and interorganizational collaboration. While IOS use and collaboration are decisions that cannot be revised easily, information sharing can be started and terminated with less necessary adjustments and in a more flexible way. Second, this result may by due to particular market conditions in Austria. As the market is small, trust, relationship, and power may generally play a different role than in the United States, where most of the previous studies have been carried out. In particular, the small Austrian FMCG market may be characterized by more homogenous attitudes toward the top five trading partners that were considered in the study. As there is a high consolidation among Austrian FMCG retailers, it is likely that most manufacturers have thought of the few dominating market leaders. Furthermore, cultural issues may be relevant. For example, in the Austrian FMCG market, the managers of the manufacturing and retailing firms know each other personally and stay in close contact. Third, the time elapsed between the referenced IOS adoption studies and this study could provide an explanation for the differences. While most studies on IOS adoption and collaboration have been carried out in the 1990s and early 2000s (see the second section), the study at hand was performed in 2006. Between these dates, the concept of supply chain management, IOS use, and interorganizational collaboration has diffused and gained importance. Therefore, mutual trust and interorganizational relationship may have increased and thus lost some relevance as an antecedent of information sharing.

Concerning the economic perception of information sharing, the hypothesized impact of benefit on strategic information-sharing behavior could be confirmed. [H.sub.8a], which assumed a positive impact of perceived benefits on information sharing, was supported due to a significant path coefficient of 0.211. Similarly, operational information sharing is influenced by perceived benefits with a path coefficient of 0.203. Like related findings on the use of IOS, these hypotheses also confirm the relevance of perceived benefits for a certain organizational behavior. The negative impact of perceived costs on information-sharing behavior ([H.sub.9a] and [H.sub.9b]) could, however, not be supported. There is no indication that perceived costs would hinder firms from practicing information sharing.

Conclusion

Contribution and implications

The presented empirical study has revealed that key drivers of information sharing are internal factors, that is, an active information policy as well as top-management commitment (for strategic information sharing) and internal technical readiness (for operational information sharing), but also perceived benefits. However, none of the interorganizational variables could be confirmed as antecedents of information sharing in this study. Therefore, we can conclude that a firm's decision to share information is largely dominated by internal considerations. As information sharing is an interorganizational process, however, this result has important implications for its interorganizational prerequisites.



The study at hand provides several contributions to literature. First, it is one of the first empirical investigations on this subject. Although previous research has addressed this field on a conceptual basis (Moberg et al., 2002), there have been few empirical findings on the particular issue of information sharing. Therefore, this study provides first insights into a topic of considerable theoretical relevance.

Second, the critical role of internal factors as an antecedent of information sharing could be confirmed. In particular, information policy, which has not yet been investigated as an antecedent of information sharing, has successfully been introduced to the research model. As information policy has not been measured so far, we could also provide a first measurement scale for this construct. The relevance of information policy for information-sharing behavior leads to the conclusion that this theoretical direction should be further investigated.

The irrelevance of interorganizational factors for information-sharing behavior shows that the analogies between findings on IOS adoption and IOS-based collaboration activities are less important than assumed. This result clearly indicates that IOS adoption, collaboration, and information sharing are conceptually different. This insight implies that more research effort is necessary to understand further drivers of information sharing, particularly in the context of interorganizational variables.

The study also shows some managerial implications concerning opportunities for information sharing and its behavior. First, information sharing seems to be a voluntary activity and largely independent from external and technical conditions. If a firm wishes to share information with others, it has to be aware that its trading partners will only agree if they are internally predestinated for it and if they are sure to benefit from it. This implies that a firm may put much effort on convincing its trading partners to share information. Another possible approach to induce trading partners to engage in information sharing is an improvement of one's own transparency, that is, starting to disseminate information to trading partners that might enter into mutual information sharing later. Trust, a good relationship, or power does not guarantee that a firm can initiate information sharing with others. Although a positive impact could not be shown by the study, it can nevertheless be assumed that some minimum trust within an interorganizational relationship is necessary for information-sharing engagement.

Second, drivers of strategic and operational information sharing are different. Top-management commitment impacts strategic but not operational information sharing. Thus, if a firm wants to share strategic information with a partner, it has to convince the top management first. If it intends to share operational information, however, the influence of top management does not play such a decisive role; it may be recommendable to address department managers first. Another difference between strategic and operational information-sharing drivers is internal technical readiness. Internal readiness is perceived as a prerequisite for operational information sharing only. This kind of information usually is exchanged frequently and in an automated way, which requires the availability of appropriate IOS. For strategic information sharing, firms might assume that they need less sophisticated IOS as the underlying information may be available in a less structured and formalized way.

Finally, the impact of perceived benefits is confirmed in this study. Firms are ready to share information if they are sure that they will benefit from this decision. This finding provides a positive indication for potential future information-sharing activities. If the benefits of information sharing, as shown by mathematical simulations and empirical research (e.g., Lee, Padmanabhan & Whang 1997; Gavirneni 2002, Kim 2005, Diaz & Buxmann 2003, Lee, So & Tang 2000), can be clearly communicated to practice and if first movers can demonstrate the benefits of their information-sharing activities, other firms will be likely start information sharing. Initiatives such as national and international efficient consumer response (ECR) movements may serve as catalysts for information-sharing adoption.

Limitations and Suggestions for Further Research

The study at hand addresses a research question that is not largely investigated and therefore is considered a starting point for further research. There are some considerable limitations that have to be mentioned as they affect the study's validity and generalizability, and therefore should be overcome in further research on this issue. First, as the research topic is highly interdisciplinary, a stronger relation to further theories should be elaborated and the contributions by each affected theory should be investigated to a larger extent. As a result, the research model could be extended by further antecedents and thus provide more insights into information-sharing behavior. Also, the model as used in this research requires revision concerning potential control variables, such as firm size, stage in the supply chain, or role of respondent. Findings in this context would provide a better basis for recommendations for practice concerning the choice of trading partners for information-sharing activities. Besides the model variables, the model structure should be revised. Potential mediating or moderating factors should be considered in the analysis of antecedents of information sharing. For example, it is worth investigating whether there are interrelations between trust, power, and the collaborative interfirm relationship. As information-sharing behavior shows several dimensions, the model could also be extended to more different facets, for example, continuous vs. ad hoc information sharing or sharing of information with different degrees of up-do-dateness or granularity.

Further research in this field requires addressing also disadvantages and costs of information sharing. As Palmer and Markus (2000) argue, firms should not always aim at achieving a maximum of a certain activity or resource. The same is true for information sharing. Not every single firm will necessarily benefit from a maximum engagement in information sharing. Factors such as costs, risks, unequal benefit sharing, or loss of autonomy may weaken a firm's position toward its trading partners. Therefore, a stronger emphasis should be put on unfavorable impacts of information-sharing participation.

There are also methodological limitations that inhere in the study at hand. First, the variables have been measured based on self-reported information. To obtain a more objective point of view, secondary data could be used for analysis, for example, performance figures or financial statements. Another bias may occur due to the measurement of the interorganizational variables that are related to the respective top five trading partners. This questionnaire design can result in rather homogenous answers throughout the sample, although it refers to the most relevant addressees of a firm's information-sharing engagement. The research model has been tested among Austrian FMCG firms, thus the findings are related to a small market and a particular industry and cannot be generalized to other contexts. The particular market situation may result in homogenous levels of mutual trust, relative power, and embedded relationship among the surveyed firms, which may conceal a potential impact of interorganizational variables on information-sharing behavior. Thus, the model should be validated in further settings, that is, other countries, other industries, and other stages in the supply chain. The sample size is a noteworthy limitation, thus following research activities should target larger sample sizes. A larger sample size would also allow analyzing whether there are different impacting factors between firms that apply IOS and those that do not by splitting the sample into subgroups. The study should also address the perspective of internationalization by accounting for cross-border information sharing as well. With increasing globalization, cross-border information sharing is expected to gain importance (McTavish, 2005), which raises the complexity of the research field by adding another dimension to it.

ACKNOWLEDGMENT

The author would like to thank the reviewers for their valuable suggestions for improvement. The author also thanks Hans Robert Hansen from the Vienna University of Economics and Business Administration and Narcyz Roztocki from the State University of New York for their invaluable remarks and suggestions, which considerably improved the research design and conceptualization and therefore the overall quality of the article. Thanks are also due to Jonathan Palmer, Mason School of Business in Williamsburg, for his remarks on the questionnaire. The survey would not have been possible without the comprising support by GS1 Austria and ECR Austria, therefore the author expresses her gratitude to Eva Maria Burian-Braunstorfer, managing director of GS1 Austria, and Nikolaus Hartig, GS1 Austria and cochairman of ECR Austria.

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Maria Madlberger is assistant professor at the Institute for Management Information Systems at the Vienna University of Economics and Business Administration in Austria. She holds a degree in commerce (master studies) and social and economic sciences (PhD). Prior to her academic career she was a specialized journalist at a trade journal addressing retailers and brand manufacturers in the Austrian consumer goods sector. Madlberger has authored two books and she published in several journals and conferences including Electronic Markets, Information Age, International Journal of Physical Distribution and Logistics Management, Journal of Electronic Commerce in Organizations, Wirtschaftsinformatik, Americas Conference on Information Systems, European Conference on Information Systems, Hawaii International Conference on Systems Sciences, and Pacific Asia Conference on Information Systems. She is associate editor of the Electronic Commerce Research Journal and member of the editorial review board of the Information Resources Management Journal. Her research interests include interorganizational systems, interfirm collaboration in supply chain management, RFID application, e-commerce b2b and b2c, and multi-channel retailing.

Maria Madlberger, Vienna University of Economics and Business Administration, Austria


APPENDIX

Questionnaire Items

Top Management Commitment

COMM01 Top management considers Grover (1993); Ranganathan,
information sharing Dhaliwal, & Teo (2004)
important to the firm.

COMM02 Information sharing is a Developed by author
fixed part of our
information technology
management.

COMM03 If necessary, our firm Premkumar & Ramamurthy
invests funds in (1995); Soliman & Janz
information sharing. (2004)

COMM04 Optimizing processes along Developed by author
the whole supply chain is
an important topic to our
firm.

COMM05 Information sharing with Developed by author
trading partners is
considered a basis for
process optimization
along the whole supply
chain.

COMM06 Our top management is Premkumar & Ramamurthy
willing to make (1995); Soliman & Janz
compromises for the (2004)
optimization of processes
along the supply
chain.

COMM07 Our top management engages Moberg et al. (2002)
in making investments
in information sharing.

COMM08 The extent of information Developed by author
sharing is subject to top
management's decision.

COMM09 Our top management knows Ranganathan et al.
the economic value of (2004); Soliman &
information sharing for Janz (2004)
the firm.

Active Information Policy

INFPOL04 Our firm publishes Developed by author
information that is
relevant to trading
partners on the Web
site.

INFPOL05 It is part of our Developed by author
corporate culture to
communicate externally
our activities.

INFPOL06 Our firm regularly Developed by author
informs media actively
and passively about
current activities and
developments.

Internal Technical Readiness

INTRDY01 Our firm has electronic Barua, Konana, Whinston,
linkages to share & Yin (2004); Bharadwaj
information with et al. (1998)
trading partners.

INTRDY02 Our firm conducts Bharadwaj et al. (1998)
IT-based collaboration
with its trading
partners.

INTRDY03 Our firm possesses an Bharadwaj et al. (1998)
IT infrastructure that
is sufficient for
information sharing.

INTRDY04 Our firm keeps its IT Developed by author
infrastructure up to
date.

INTRDY05 Our firm has enough Bharadwaj et al. (1998)
skilled personnel for
further extending the
IT infrastructure.

INTRDY06 Our IT infrastructure Developed by author
is so powerful that
it provides a
competitive advantage
to our firm.

Embedded Relationship with Partners

RELAT01 Our firm has an Developed by author
intensive relationship based on Chatfield &
with its trading Yetton (2000) and Uzzi
partners. (1997)

RELAT02 The relationship Moberg et al. (2002)
between our firm and
its trading partners
is long-term oriented.

RELAT03 The relationship Developed by author
between our firm and based on Chatfield &
its trading partners Yetton (2000) and Uzzi
is defined by (1997)
contractual agreements.

RELAT04 There is an intensive Developed by author
personal contact based on Chatfield &
between our firms' and Yetton (2000) and Uzzi
the trading partners' (1997)
contact persons.

RELAT05 Our trading partners Developed by author
have an intensive based on Chatfield &
relationship with Yetton (2000) and Uzzi
our firm. (1997)

Trust in Trading Partners

TRUST01 Our trading partners Doney & Cannon (1997);
keep their promises. Moberg et al. (2002)

TRUST02 Our trading partners Doney & Cannon (1997);
are honest. Moberg et al. (2002)

TRUST04 We believe that our Doney & Cannon (1997);
trading partners are Moberg et al. (2002)
genuinely concerned
about our welfare.

TRUST05 Our trading partners Doney & Cannon (1997);
only care for their Moberg et al. (2002)
own benefits (reverse).

TRUST06 Our trading partners Doney & Cannon (1997);
keep our best Moberg et al. (2002)
interests in mind.

Trading Partners' Relative Power

POWER01 Our firm follows the Premkumar & Ramamurthy
trading partners' (1995); Soliman & Janz
requirements concerning (2004)
electronic data
exchange (reverse).

POWER02 Our firm cannot switch Teo et al. (2003)
to other trading
partners easily
(reverse).

POWER03 Our firm could replace Teo et al. (2003)
lost trading partners
easily.

POWER04 Our trading partners Soliman & Janz (2004)
determine the conditions
of collaboration
(reverse).

POWER05 Our trading partners Teo et al. (2003)
are important firms in
our industry (reverse).

Trading Partners' Technical Readiness

TPRDY01 Our trading partners Barua et al. (2004);
have electronic linkages Bharadwaj et al.
to share information (1998)
with their trading
partners.

TPRDY02 Our trading partners Bharadwaj et al. (1998)
conduct IT-based
collaboration with
their trading partners.

TPRDY03 Our trading partners Bharadwaj et al. (1998)
possess an IT
infrastructure that
is sufficient for
information sharing.

TPRDY04 Our trading partners Developed by author
prefer compatible
industry standards
to individual
solutions.

TPRDY05 Our trading partners Bharadwaj et al. (1998)
keep their IT
infrastructure up
to date.

Perceived Benefits of Information
Sharing

ISBNFT01 Sales increase Developed by author

ISBNFT02 Cost savings Saunders & Clark (1992)

ISBNFT03 Reduced inventory Saunders & Clark (1992)
levels

ISBNFT04 Reduced out-of- Saunders & Clark (1992)
stock situations

ISBNFT05 Higher delivery Saunders & Clark (1992)
accuracy

ISBNFT06 Shorter delivery Saunders & Clark (1992)
time

ISBNFT07 Better delivery Saunders & Clark (1992)
conditions

ISBNFT08 Better pricing Saunders & Clark (1992)
conditions

ISBNFT09 Important Developed by author
prerequisite for
efficient
collaboration in
the supply chain

Perceived Costs of Information
Sharing

ISCOST01 Requires generally Developed by author
considerable IT
investments

ISCOST02 Future or follow-up Saunders & Clark (1992)
investments that cannot
be assessed at present

ISCOST03 Technical security Saunders & Clark (1992)
issues

ISCOST04 Additional workload Saunders & Clark (1992)
or personnel
requirements

ISCOST05 Increase of operational Developed by author
IT costs

ISCOST06 Pays only if conducted Developed by author
with a minimum number of
trading partners

ISCOST07 Pays only if conducted Developed by author
with important trading
partners

Operational Information-Sharing
Behavior

OISB01 Advanced shipping Moberg et al. (2002);
notice Tan & Wang (2001); Van
de Ven & Ferry (1980)

OISB02 Order status Moberg et al. (2002);
Tan & Wang (2001); Van
de Ven & Ferry (1980)

OISB03 Quality-assurance data Developed by author
(suggested by
practitioners)

OISB04 Sales forecasts Patnayakuni et al.
(2006); Tan & Wang
(2001)

OISB05 Promotional plans Developed by author
(suggested by
practitioners)

Strategic Information-Sharing
Behavior

SISB01 New target markets Moberg et al. (2002);
Van de Ven & Ferry
(1980)

SISB02 New product development Moberg et al. (2002);
Van de Ven & Ferry
(1980)

SISB03 Distribution strategies Moberg et al. (2002);
Van de Ven & Ferry
(1980)

SISB04 Promotional strategies Moberg et al. (2002);
Van de Ven & Ferry
(1980)

SISB05 Pricing strategies Moberg et al. (2002);
Van de Ven & Ferry
(1980)

SISB06 Market research data Feldberg & van der
Heijden (2003)

SISB07 Production batches Developed by author
(suggested by
practitioners)

SISB08 Forecasting data Patnayakuni et al.

Table 1. Operationalizations of information sharing in literature

Operationalizations Source
of Information
Sharing

Inventory levels Feldberg & van der Heijden (2003); Li, Shaw, &
Tan (2000); Moberg, Cutler, Gross, & Speh (2002);
Patnayakuni, Rai, & Seth (2006); Tan & Wang
(2001); Van de Ven & Ferry (1980)

POS sales data/ Feldberg & van der Heijden (2003); Patnayakuni et
scanningdata al. (2006)

Outlet data Feldberg & van der Heijden (2003)

Advanced shipping Moberg et al. (2002); Tan & Wang (2001); Van de
notice Ven & Ferry (1980)

Order status Moberg et al. (2002); Tan & Wang (2001); Van de
Ven & Ferry (1980)

Production Moberg et al. (2002); Patnayakuni et al. (2006);
schedules Van de Ven & Ferry (1980)

Market research Feldberg & van der Heijden (2003)
data

Sociodemographic Feldberg & van der Heijden (2003)
data

Loyalty-card data Feldberg & van der Heijden (2003)

Sales forecasts Patnayakuni et al. (2006); Tan & Wang (2001)

Demand data Li et al. (2000)

New target markets Moberg et al. (2002); Van de Ven & Ferry (1980)

New product Moberg et al. (2002); Van de Ven & Ferry (1980)
development

Distribution Moberg et al. (2002); Van de Ven & Ferry (1980)
strategies

Promotional Moberg et al. (2002); Van de Ven & Ferry (1980)
strategies

Pricing strategies Moberg et al. (2002); Van de Ven & Ferry (1980)

Table 2. Sample description

Annual Sales Employees

Less than 10 million 42.7% Less than 50 56.3%
EUR
10-50 million EUR 31.2% 50-250 27.2%
50-100 million EUR 10.2% 250-500 3.8%
100-500 million EUR 10.8% 500-1,000 4.4%
500-1,000 million 2.5% More than 8.2%
EUR 1,000
More than 1,000 2.5%
million EUR

Geographic Area Stage in Supply Chain

Austria only 48.7% Manufacturer 44.2%
Mainly Austria 39.7% Retailer 38.3%
Mainly outside of 11.5% Distributor 17.5%
Austria

Industry Position of Respondent

Groceries 67.9% CEO/owner 57.8%
Drug 11.5% Sales manager 13.7%
Others 20.5% Others 28.5%

Table 3. Measurement scales

Variable Description No. of Items Cronbach's
Alpha

OISB Operational information-sharing 8 0.841%
behavior
SISB Strategic information-sharing 5 0.938
behavior
COMM Top-management commitment 9 0.934
INFPOL Active information policy 3 0.805
INTRDY Internal technical readiness 6 0.941
TRUST Trust in trading partners 5 0.907
RELAT Highly embedded relationship 5 0.904
with trading partners
POWER Trading partners' relative 5 0.802
power
2TPRDY Trading partners' technical 5 0.930
readiness
ISBNFT Perceived benefits of 9 0.930
information sharing
ISCOST Perceived costs of 7 0.883
information sharing

Table 4. PLS analysis results

Path Hypothesis
Hypothesis Coefficient T Value Decision

[H.sub.1a]: COMM -> SISB 0.268 * 2.555 Supported

[H.sub.1b]: COMM -> OISB 0.098 0.825 Rejected

[H.sub.2a]: INFPOL -> SISB 0.265 * 2.246 Supported

[H.sub.2b]: INFPOL -> OISB 0.237 * 2.246 Supported

[H.sub.3a]: INTRDY -> SISB 0.054 0.427 Rejected

[H.sub.3b]: INTRDY -> OISB 0.257 * 1.905 Supported

[H.sub.4a]: TRUST -> SISB -0.066 0.620 Rejected

[H.sub.4b]: TRUST-> OISB 0.107 1.060 Rejected

[H.sub.5a]: RELAT-> SISB 0.056 0.435 Rejected

[H.sub.5b]: RELAT -> OISB -0.047 0.408 Rejected

[H.sub.6a]: POWER-> SISB 0.077 0.586 Rejected

[H.sub.6b]: POWER -> OISB 0.079 0.693 Rejected

[H.sub.7a]: TPRDY -> SISB -0.013 0.109 Rejected

[H.sub.7b]: TPRDY -> OISB -0.053 0.483 Rejected

[H.sub.8a]: ISBNFT -> SISB 0.211 * 1.795 Supported

[H.sub.8b]: ISBNFT -> OISB 0.203 * 1.650 Supported

[H.sub.9a]: ISCOST -> SISB 0.025 0.242 Rejected

[H.sub.9b]: ISCOST -> OISB -0.024 0.230 Rejected

* significant at 0.05 level

Source Citation:Madlberger, Maria. "What drives firms to engage in interorganizational information sharing in supply chain management?." International Journal of e-Collaboration 5.2 (April-June 2009): 18(25). Computer Database. Gale. BROWARD COUNTY LIBRARY. 3 May 2009
.

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